Explained variation in a model of therapeutic decision making is partitioned across patient, physician, and clinic factors

J Clin Epidemiol. 2006 Jan;59(1):18-25. doi: 10.1016/j.jclinepi.2005.07.005. Epub 2005 Nov 7.


Background and objective: Data on therapeutic decision making have a multilevel structure that can include patient-, provider-, and facility-level variables. A statistical method is presented for attributing explained variation in patient care to different levels of aggregation in a multilevel model with the aim of prioritizing and targeting quality improvement interventions.

Study design and setting: The proposed method is used in an analysis of adherence to evidence-based guidelines for the care of patients at risk of osteoporosis. Explained variation from a multilevel model of appropriate care is partitioned across patient-, physician-, and clinic-level factors.

Results: The combination of patient, physician, and clinic factors explained 20.0% of the variation in patient care. Individual physician effects explained 14.0% of the variation in the data; however, more than half of this explained variation could have been attributed to the individual clinic effect. Patient fixed effects alone explained 13.4% of the variation in the observed clinical decisions.

Conclusion: The proposed approach is an intuitive and statistically valid method for attributing explained variation in a multilevel analysis of therapeutic decision making.

Publication types

  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Administration, Oral
  • Aged
  • Decision Making*
  • Evidence-Based Medicine
  • Female
  • Fractures, Bone / epidemiology
  • Glucocorticoids / administration & dosage
  • Guideline Adherence
  • Humans
  • Male
  • Middle Aged
  • Models, Statistical
  • Osteoporosis / prevention & control*
  • Patient Participation*
  • Physician's Role
  • Physician-Patient Relations
  • Risk Factors
  • Smoking


  • Glucocorticoids